Evidence map›Paper›PMID 30797065›Full record

ArticleThe Journal of molecular diagnostics : JMD2019

A Model Information Management Plan for Molecular Pathology Sequence Data Using Standards: From Sequencer to Electronic Health Record.

Walter S Campbell, Alexis B Carter, Allison M Cushman-Vokoun, Timothy C Greiner, Rajesh C Dash, Mark Routbort, Monica E de Baca, James R Campbell

Abstract read
In one paragraph

Article in The Journal of molecular diagnostics : JMD, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. HL7 FHIR-based tools and initiatives to support clinical research: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2022
    Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Walter S CampbellDepartment of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, Nebraska. Electronic address: wcampbel@unmc.edu.
Alexis B CarterDepartment of Pathology, Children's Healthcare of Atlanta, Atlanta, Georgia.
Allison M Cushman-VokounDepartment of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, Nebraska.
Timothy C GreinerDepartment of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, Nebraska.
Rajesh C DashDepartment of Pathology, Duke University Health System, Durham, North Carolina.
Mark RoutbortDepartment of Hematopathology, University of Texas MD Anderson Cancer Center, Houston, Texas.
Monica E de BacaMedical Laboratory Associates, Lynnwood, Washington.
James R CampbellDepartment of Internal Medicine, University of Nebraska Medical Center, Omaha, Nebraska.

Funding

Deploying ONC national Standards in Support of Metadata for Big Data Research Warehouse Management of Repurposed Laboratory, Pathology & Patient Findings Data From the EHR.U01HG009455 · NHGRI · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI CAMPBELL, WALTER SCOTT · 2016 to 2018
$1.7M
NHGRI NIH HHS U01 HG009455
6 · The paper itself

Abstract

Incorporating genetic variant data into the electronic health record (EHR) in discrete computable fashion has vexed the informatics community for years. Genetic sequence test results are typically communicated by the molecular laboratory and stored in the EHR as textual documents. Although text documents are useful for human readability and initial use, they are not conducive for data retrieval and reuse. As a result, clinicians often struggle to find historical gene sequence results on a series of oncology patients within the EHR that might influence the care of the current patient. Second, identification of patients with specific mutation results in the EHR who are now eligible for new and/or changing therapy is not easily accomplished. Third, the molecular laboratory is challenged to monitor its sequencing processes for nonrandom process variation and other quality metrics. A novel approach to address each of these issues is presented and demonstrated. The authors use standard Health Level 7 laboratory result message formats in conjunction with international standards, Systematized Nomenclature of Medicine Clinical Terms and Human Genome Variant Society nomenclature, to represent, communicate, and store discrete gene sequence data within the EHR in a scalable fashion. This information management plan enables the support of the clinician at the point of care, enhances population management, and facilitates audits for maintaining laboratory quality.

Indexed as

Electronic Health RecordsBase SequenceHigh-Throughput Nucleotide SequencingHumansPathology, MolecularReference StandardsSequence Analysis, DNATerminology as Topic

Identifiers

PMID30797065
PMCPMC6521887

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.